丘脑底核
脑深部刺激
步态
帕金森病
医学
物理医学与康复
刺激
步态分析
评定量表
疾病
内科学
心理学
发展心理学
作者
Jakub Żak,Kelvin L. Chou,Parag G. Patil,Karlo A. Malaga
标识
DOI:10.3171/2024.10.jns241470
摘要
OBJECTIVE Subthalamic nucleus (STN) deep brain stimulation (DBS) alleviates the motor symptoms of Parkinson disease (PD). However, a generalized targeting approach may lead to suboptimal outcomes for patients with diverse symptoms. Volume of tissue activation (VTA) modeling can be used to compute the spatial extent of stimulation relative to specific neural structures to assess clinical outcomes. Better outcomes for gait disturbances may be obtained by stimulating regions within or around the STN. This study aimed to determine the optimal stimulation region within or around the STN to improve gait disturbances in PD. METHODS Forty PD patients who underwent bilateral STN DBS were analyzed retrospectively. The therapeutic VTA of 72 implants was calculated to quantify STN and external (non-STN) activation in different regions. Stepwise regression was used to evaluate associations between stimulation location and gait symptom improvement (based on the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale). Implants grouped by stimulation location were compared according to symptom improvement using the Kruskal-Wallis test. Electrode position (relative to the STN) was examined for comparison. RESULTS Significant positive associations between anterior STN activation and gait (p = 0.03) and total gait improvement (p = 0.01) were found. Significant differences in freezing of gait (FoG) (p = 0.03) and total gait (p = 0.02) were also found when the majority anterior and majority posterior STN activation groups were compared. For external activation, a significant positive association between anterior external activation and FoG (p = 0.02) was found. No significant relationship between electrode position and gait symptoms was found. CONCLUSIONS More anterior STN DBS may benefit patients whose primary symptoms include gait disturbances. This study demonstrates the utility of VTA modeling and highlights the importance of patient- and symptom-specific targeting.
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